一种面向室内定位的基站选择优化方法

基于蜂窝网的室内定位由于与通信网络共用基础设施,因此具有覆盖范围广、无需基础设施再投资等突出优点,已成为电信运营商级室内定位的首选,是5G通信领域的研究热点之一。在蜂窝网室内定位场景中,基站的布局将直接影响接收首径的数量、到达时间TOA(Time of Arrivaling)和测量误差等要素,从而影响定位精度。据此,文中提出一种面向室内定位的基站选择优化方法,以减小由于基站布局引入的误差。首先,引入TOA信息去除TDOA定位的虚定位点；其次,针对不同基站选择方案得到的定位结果,利用二次聚类的思想去除孤立点,并根据聚类结果中样本节点数量最多的类确定定位点的位置。实验结果表明,与其他优化方法相比,所提方法的室内定位平均误差降低了15.49%。

Base Station Selection Optimization Method Oriented at Indoor Positioning

Indoor positioning based on the cellular network has become the preferred carrier-class method.Due to the common infrastructure of the communication network,it has a wide range of coverage and it is without the need for reinvestment of infrastructure,which has become one of hot spots in the field of 5G communication.In the cellular positioning scene of network indoor,the layout of station will directly affect the number of the first acceptance diameter,arriving time TOA (Time of Arrival),measurement error and so on,then it will affect the positioning accuracy.A base station selection optimization algorithm for indoor location was proposed,which reduces the deviation due to the base station layout.Firstly,an indoor three-dimensional positioning model with error suppression is proposed to suppress the inaccuracy of single model localization.TOA information is used to suppress the error caused by the virtual locating point in the TDOA model.Secondly,according to the results of the selection of different base stations,the isolated point are removed by the idea of secondary clustering,position of the positioning point is determined according to the class with the largest number of sample nodes in the clustering result.The experimental results show that the base station selection optimization algorithm reduces the average deviation of indoor positioning by 15.49% compared with other optimization algorithms.